Date of Award

2009

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Psychology

First Advisor

Hoza, Betsy

Abstract

Attention-Deficit/Hyperactivity Disorder (ADHD) is a disorder characterized by a persistent pattern of developmentally inappropriate levels of inattention, hyperactivity, and impulsivity (American Psychiatric Association, 2000). Currently, clinicians typically utilize a multi-method assessment battery focusing on identifying the core symptoms of ADHD. Further, current recommendations for a comprehensive assessment of ADHD require a lengthy and costly evaluation protocol despite a lack of evidence supporting the incremental utility of each method. Assessment strategies exhibiting the strongest evidence of reliability and validity include symptom-based rating scales, empirically-derived rating scales, and structured diagnostic interviews (Pelham, Fabiano, & Massetti, 2005), yet, their review provided limited empirical support for this conclusion. Nonetheless, other reviews have noted the lack of research examining whether each procedure and/or method adds unique information to a diagnosis of ADHD (Johnston & Murray, 2003). In order to fill this gap in the literature, the current study examined the independent and incremental utility of multiple methods and informants in a comprehensive, “gold standard” assessment of ADHD. The sample include 185 children with ADHD (Mage =9.22, SD=.95) and 82 children without ADHD (Mage =9.24, SD=.88). Logistic regressions were used to examine the incremental contribution of each method in the prediction of consensus diagnoses derived by two Ph.D. level experts in the field of ADHD following a review of comprehensive assessment data. This study also examined the clinical utility and efficiency of diagnostic algorithms using the methods demonstrating the greatest statistical association with a diagnosis of ADHD. Finding provided an empirical support for arguments espousing the redundancy of information in a comprehensive assessment. Namely, information collected from a structured diagnostic interview was unable to significantly improve a prediction model including parent and teacher ratings (Block X2-= .91 = .64). Importantly, parent and teacher ratings on a symptom-based scale alone were able to correctly classify 265 of 267 participants. Based on these results, a diagnostic algorithm that was derived utilizing only behavioral rating scales was able to classify correctly all 267 participants. Clinical implications are highlighted and future research directions are discussed.

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